Prospective Health Technology Assessment allows early decision making for innovative health care technologies. In our recent publications a hybrid simulation approach with System Dynamics and Agent-Based Modeling has been presented. This paper presents a mechanism to generate agents dynamically from SD models and extends the previously presented hybrid approach by process-oriented Discrete Event Simulation for hospital modeling.
Several challenges of port/terminal and/or ferry company managers pertain to decisions for the justification of investments and concurrent operational tasks of roll-on/roll-off passenger (RoPax) and roll-on/roll-off (RoRo) systems. This paper explores the possible uses of Modeling and Simulation (M&S) techniques as a decision-support aid for a RoPax/RoRo system managers.
This paper describes a methodical and practical approach of hybrid model creation using the simulation tool AnyLogic. We focus on general modeling aspects and on advanced techniques using a Level-Based Architecture that help to develop large scale hybrid simulation models. An implementation of a stroke therapy use-case and its simulation results will be discussed. Finally, some practical ideas for validation will be outlined, as we experienced during the stroke use-case development.
This paper presents an agent-based model for simulating wind power systems on multiple time scales. The aim is to generate a flexible model that allows us to simulate the output of a wind farm. The model is developed using multiparadigm modelling, combining different approaches such as agent-based modelling, discrete events and dynamic systems.
This paper contains some banking issues that can be successfully resolved by the users of AnyLogic – multimethod simulation tool. The list of issues is not exhaustive, it reflects some tasks that have been discussed by XJ Technologies and AnyLogic users - banking organizations.
In many areas of science, like computer science or electrical engineering, modeling languages have been established, however, this is not the case in the field of discrete processes (Weilkiens 2006). There are two reasons which motivate such a development.
This panel seeks to initiate a discussion within the production system simulation community about a fundamental change in the way we think about, teach, and implement production system simulation. Today, production system simulation, while based on formal simulation languages, is largely an artistic process.
In the industrial engineering community, it’s a well-known adage that focusing on process can help achieve better results. In this second of a series of papers, we’ll focus on the process of simulation testing and outline how improving your testing process can lead to better results for your projects. We’ll consider model building as a software development exercise, and discuss how best practices from the broader software testing community can be applied for process improvement.